Integrate the Semgrep API with the Python API

Setup the Semgrep API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Semgrep and Python remarkably fast. Free for developers.

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Popular Semgrep and Python Actions#

Get Deployments with the Semgrep API

Returns a list of deployments. See the documentation

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Get Findings with the Semgrep API

Returns a list of findings for a specified deployment. See the documentation

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Get Projects with the Semgrep API

Returns a list of projects for a given deployment slug. See the documentation

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Update Project with the Semgrep API

Update a project on Semgrep. See the documentation

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Overview of Semgrep#

The Semgrep API enables developers to integrate powerful static code analysis within their workflows on Pipedream. Semgrep scans codebases for bugs, security issues, and code standards, making it a vital tool for maintaining code quality. On Pipedream, you can automate code reviews, enforce coding standards, and trigger alerts or actions based on scan results. By connecting Semgrep to Pipedream, you can streamline your CI/CD pipelines, notify teams of critical issues, and even auto-fix problems under certain conditions.

Connect Semgrep#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    semgrep: {
      type: "app",
      app: "semgrep",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://semgrep.dev/api/v1/deployments`,
      headers: {
        Authorization: `Bearer ${this.semgrep.$auth.api_token}`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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